Protein Classification Using Artificial Neural Networks with Different Protein Encoding Methods. - André Luis Debiaso Rossi; Maria Angelica de Oliveira Camargo-Brunetto (ISDA, 2007)

Bio-Inspired Parameter Tunning of MLP Networks for Gene Expression Analysis. - André L. D. Rossi; André C. P. L. F. de Carvalho; Carlos Soares (HIS, 2008)

Bioinspired Parameter Tuning of MLP Networks for Gene Expression Analysis: Quality of Fitness Estimates vs. Number of Solutions Analysed. - André L. D. Rossi; Carlos Soares; André C. P. L. F. de Carvalho (ICONIP (2), 2008)

Bio-inspired Optimization Techniques for SVM Parameter Tuning. - André L. D. Rossi; Luis Debiaso; André Carlos Ponce de Leon Ferreira de Carvalho (SBRN, 2008)

Combining Meta-learning and Search Techniques to SVM Parameter Selection. - Taciana A. F. Gomes; Ricardo Bastos Cavalcante Prudêncio; Carlos Soares; André L. D. Rossi; André Carlos Ponce de Leon Ferreira de Carvalho (SBRN, 2010)

Using Genetic Algorithms to Improve Prediction of Execution Times of ML Tasks. - Rattan Priya; Bruno Feres de Souza; André L. D. Rossi; André Carlos Ponce de Leon Ferreira de Carvalho (HAIS (1), 2012)

Meta-Learning for Periodic Algorithm Selection in Time-Changing Data. - André Luis Debiaso Rossi; André C. P. L. F. de Carvalho; Carlos Soares (SBRN, 2012)

Combining meta-learning and search techniques to select parameters for support vector machines. - Taciana A. F. Gomes; Ricardo Bastos Cavalcante Prudêncio; Carlos Soares; André L. D. Rossi; André C. P. L. F. de Carvalho (Neurocomputing, 2012)

Predicting execution time of machine learning tasks for scheduling. - Rattan Priya; Bruno Feres de Souza; André L. D. Rossi; André Carlos Ponce de Leon Ferreira de Carvalho (Int. J. Hybrid Intell. Syst., 2013)

Metalearning for algorithm selection in data strams. - André Luis Debiaso Rossi (2013)

MetaStream: A meta-learning based method for periodic algorithm selection in time-changing data. - André Luis Debiaso Rossi; André Carlos Ponce de Leon Ferreira de Carvalho; Carlos Soares; Bruno Feres de Souza (Neurocomputing, 2014)

To tune or not to tune: Recommending when to adjust SVM hyper-parameters via meta-learning. - Rafael Gomes Mantovani; André Luis Debiaso Rossi; Joaquin Vanschoren; Bernd Bischl; André C. P. L. F. de Carvalho (IJCNN, 2015)

Effectiveness of Random Search in SVM hyper-parameter tuning. - Rafael Gomes Mantovani; André Luis Debiaso Rossi; Joaquin Vanschoren; Bernd Bischl; André C. P. L. F. de Carvalho (IJCNN, 2015)

Meta-learning Recommendation of Default Hyper-parameter Values for SVMs in Classification Tasks. - Rafael Gomes Mantovani; André L. D. Rossi; Joaquin Vanschoren; André C. P. L. F. de Carvalho (MetaSel@PKDD/ECML, 2015)

Deep learning for biological image classification. - Carlos Affonso; André Luis Debiaso Rossi; Fábio Henrique Antunes Vieira; André Carlos Ponce de Leon Ferreira de Carvalho (Expert Syst. Appl., 2017)

A guidance of data stream characterization for meta-learning. - André Luis Debiaso Rossi; Bruno Feres de Souza; Carlos Soares; André Carlos Ponce de Leon Ferreira de Carvalho (Intell. Data Anal., 2017)

Dimensionality Reduction for the Algorithm Recommendation Problem. - Edesio Alcobaça; Rafael Gomes Mantovani; André L. D. Rossi; André C. P. L. F. de Carvalho (BRACIS, 2018)

A meta-learning recommender system for hyperparameter tuning: Predicting when tuning improves SVM classifiers. - Rafael Gomes Mantovani; André L. D. Rossi; Edesio Alcobaça; Joaquin Vanschoren; André C. P. L. F. de Carvalho (Inf. Sci., 2019)

Frontmatter. - Angelo Brayner; Maristela Holanda; André L. D. Rossi (J. Inf. Data Manag., 2019)

Harnessing Particle Swarm optimization Through Relativistic Velocity. - Mateus Roder; Gustavo Henrique de Rosa; Leandro Aparecido Passos; João Paulo Papa; André Luis Debiaso Rossi (CEC, 2020)

N-BEATS-RNN: deep learning for time series forecasting. - Attilio Sbrana; André Luis Debiaso Rossi; Murilo Coelho Naldi (ICMLA, 2020)

Algorithm Recommendation for Data Streams. - Jáder M. C. de Sá; André L. D. Rossi; Gustavo E. A. P. A. Batista; Luís Paulo F. Garcia (ICPR, 2020)

Rethinking Default Values: a Low Cost and Efficient Strategy to Define Hyperparameters. - Rafael Gomes Mantovani; André Luis Debiaso Rossi; Edesio Alcobaça; Jadson Castro Gertrudes; Sylvio Barbon Junior; André Carlos Ponce de Leon Ferreira de Carvalho (CoRR, 2020)

ALO: AI for Least Observed People. - Shamim Al Mamun; Mohammad Eusuf Daud; Mufti Mahmud; M. Shamim Kaiser; André Luis Debiaso Rossi (AII, 2021)

From Actions to Events: A Transfer Learning Approach Using Improved Deep Belief Networks. - Mateus Roder; Jurandy Almeida; Gustavo Henrique de Rosa; Leandro A. Passos; André L. D. Rossi; João P. Papa (SSCI, 2021)

Micro-MetaStream: Algorithm selection for time-changing data. - André Luis Debiaso Rossi; Carlos Soares; Bruno Feres de Souza; André Carlos Ponce de Leon Ferreira de Carvalho (Inf. Sci., 2021)

Energy-Based Dropout in Restricted Boltzmann Machines: Why Not Go Random. - Mateus Roder; Gustavo Henrique de Rosa; Victor Hugo C. de Albuquerque; André L. D. Rossi; João P. Papa (IEEE Trans. Emerg. Top. Comput. Intell., 2022)

Feature Selection and Hyperparameter Fine-Tuning in Artificial Neural Networks for Wood Quality Classification. - Mateus Roder; Leandro Aparecido Passos; João Paulo Papa; André Luis Debiaso Rossi (BRACIS (2), 2023)

Financial Distress Prediction in an Imbalanced Data Stream Environment. - Rubens Marques Chaves; André Luis Debiaso Rossi; Luís Paulo Faina Garcia (HAIS, 2023)

Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms. - Rafael Gomes Mantovani; Tomás Horváth; André L. D. Rossi; Ricardo Cerri; Sylvio Barbon Junior; Joaquin Vanschoren; André C. P. L. F. de Carvalho (Data Min. Knowl. Discov., 2024)